The significance of Prayer and its healing power. Or, playing Go with God

All the religious traditions raise endless prayers for living aids, those spread all over human lives. Without the hope that in all our needs and trials we have ‘someone’ to second us, so powerful that can help us overcome anything that stands in our path (more accurate 'against our wish'), most religious traditions would not be given any consideration, for humans become religious mostly when falling into a trial of life. By this hope religiousness flourishes and religious offer develops. Still, there is another way of considering prayer, one of spiritual becoming, diverse, and at the same time equally tender. It doesn’t offer goods, or aids, or anything specific, instead, it is professed by many spiritual persons that stood in the divine’s company. Theologians call it apophasis, spiritualists call it contemplation. Non-believers assert that the ‘responses’ of prayers followed by the ‘altering’ of reality is merely a mental projection, a Placebo effect of believing in prayer’s effect, or even just a mere coincidence. Either way, we need to learn prayer’s genuine significance and what it really provides. As for the subtitle, it is an allusion to the ancient game of Go whose main skill is to 'know' in advance tens, hundreds, or even infinite moving variables with their follow-ups, so you can be prepared and have a prepared answer every time to any move the teammate would make.

Just what are we doing when we’re describing AI? Harvey Sacks, the commentator machine, and the descriptive politics of the new artificial intelligence

In dialogue with the work of Heather Love and colleagues, this article makes use of a peculiar ‘descriptive assemblage’ proposed by Harvey Sacks (1963) – that of the ‘commentator machine’ – to open up issues of ‘descriptive politics’ in the field of contemporary Artificial Intelligence (AI). We do so by reviewing the gameplay of Google DeepMind’s AlphaGo – an algorithm designed to outperform human players at the game of Go – with a focus on the incongruities of the much discussed, indeed (in)famous ‘move 37’ in a human-versus-machine challenge match in 2016 (e.g. Silver et al., 2017). Looking at move 37 in conjunction with the various layers of commentary that came to be woven around it, we explore the kinds of descriptive work involved in characterising the move, the troubles that work reveals and what we can learn about the practices and politics of description from encounters with ‘New AI’ applications like AlphaGo.